(auteur) We present a customized version of GGIS (Quantum GIS) integrating OTB (Orfeo Toolbox) software that allows the processing of Sentinel-1 IW time series acquisitions in GRD products format. The processing is dedicated to radar non specialists that are concerned with vegetation monitoring such as Land cover estimation, or deforestation and forest degradation areas detection.

(Introduction) In wetlands, hydrological regimes determine values of functions and ecosystem services. If hydrological regimes of wetlands are now widely handled by environmental managers, its impacts on both floods and vegetation dynamics are still unexplored. Simultaneously, the new Earth observation Sentinel-1 constellation, allowing all weather radar acquisitions with high temporal and spatial resolution appears as a promising opportunity for the monitoring of wetlands. In the same time, this study aims at (i) evaluating the ability of a Sentinel-1 time for the detection and monitoring of flood areas at 1:50 000 scale across a 100 000 hectares marsh; (ii) exploring the relation between the hydrological dynamic and ecological processes.

(auteur) SAR data are well suited for the retrieval of biomass from vegetated areas. In particular, the ability of low frequencies to deeply penetrate dense vegetation, allows P band radar data to retrieve high biomass levels that can be encountered over forests, where other frequencies show their limitations. The BIOMASS mission, consisting in the launch of a P band SAR sensor, has been selected by ESA as the 7th Earth Explorer mission, will allow to estimate the world’s forest biomass and its changes. However, forests observe strong spatial differences in terms of structure or surface topography. These differences induce significant changes of the scattering mechanism occurring within a resolution cell. At global scale, the differences are obvious (for example between boreal and tropical regions), but at regional scale, strong differences can also be observed (for example gallery forests within savannahs, forest edges, or changes due to surface topography). The consideration of these changes is a major issue to improve the robustness of the inversion algorithm in order to reduce the errors of the biomass estimations. Up to now, no unique inversion method has been developed, that would be valid over the wide variety of forests types. An alternative is to propose a classification method that will allow to discriminate between forest types in terms of radar scattering behavior in order to apply the best suited algorithm. This is the aim of the present study. The focus is put on the analysis of the different polarimetric indices that can be derived from the fully polarimetric data acquired during the BIOMASS mission. Then the contribution of other data that should be concomitant to the BIOMASS mission, such as Sentinel-1 at C band or PALSAR2 at L band will also be investigated. This study will be based on the analysis of P band SAR data acquired during airborne campaigns other boreal (BioSAR 1 and 2) and tropical (TropiSAR, AfriSAR) forests, over a wide range of biomass value and terrain conditions.

(auteur) Included in the larger Guiana Shield ecosystem, Suriname, Guyana, French Guiana and the Brazilian state of Amapá possess one of the largest continuous tracts of pristine forest in the world. Under little threat until fifteen years ago, deforestation and forest degradation are of increasing concern in the region. Gold mining activities driven by the sustained increase of gold price has experienced a significant boom and represents nowadays one of the main driver. The pollution of rivers and streams by mercury used in small-scale gold mining is also expanding, which increases risks to local population health and freshwater biodiversity. In 2010, the French National Forest Office (ONF) showed by using optical satellite images at medium and high resolution (HR) that gold mining activities’ impacts on forest cover and freshwater increased approximately by a factor three in the region between 2001 and 2008. More recently, Alvarez-Berríos et al. (2015) pointed out a sustained acceleration of deforestation caused by gold mining in the Guiana shield between 2007 and 2013. However, this study which was performed using low resolution data at the scale of South America has limited capacity to detect gold mining, especially in the high forest cover of Guiana Shield where small- and medium-scale operations account for most of the deforestation. To overcome this limitation, the REDD+ for the Guiana Shield project conducted a study co-funded by WWF Guianas to update for 2014 the ONF 2001-2008 results, using optical multi-sensors data at medium and high resolution. The study was carried out following a unique collaborative and participatory approach involving a team of experts from the forestry and environmental services of each territory, namely SEMA (Amapá-Brazil), ONF (French Guiana-France), GFC (Guyana), and SBB (Suriname). The results confirmed the rapid expansion of the activity in the region where more than 92,000 ha were newly deforested between 2008 and 2014, compared to approximately 46,000 ha during the period 2001-2008. In 2014, more than 9,000 km of waterways were in direct contact with mining sites, which is approximately 6.5 times more than in 2001. Although a reliable, accurate and robust regional methodology has been developed and operationally implemented, the frequent and widespread cloud cover of the Guianan moist forest region represents a challenge for the use of optical HR data. The need to process time series of satellite images in most areas to reduce cloud cover is time-consuming. Despite processing more than two hundreds images, 3.6% of the study area remained masked by clouds. The recent free access to SAR HR Sentinel-1 data offers great opportunities to improve the process. SAR sensors can peer through clouds and their sensitivity to soil moisture can help to better detect small-scale mining sites. Therefore, the REDD+ for the Guiana Shield project has started to build capacities in the region on SAR image interpretation and processing using the Sentinel Application Platform (SNAP). A first mosaic of Sentinel-1 data covering Suriname, Guyana, French Guiana and the Brazilian state of Amapá has been created and automated pre-processing steps have been developed. The integration of Sentinel-1 data in the regional gold mining monitoring system has been successfully tested in four study sites, one in each country. The coming free access to optical HR Sentinel-2 data opens even more perspectives towards the development of cost-effective monitoring systems in the region, especially valuable in the context of REDD+. This paper first presents the results of the impact of gold mining activities on the forest cover and freshwater for 2014 and shows the evolution since 2001. Secondly, it provides the first outcomes towards the development of time- and cost-efficient forest monitoring systems in the region.